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- Author or Editor: A. Protat x
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Abstract
The objective of this paper is to assess the performances of the proposed ice water content (IWC)–radar reflectivity Z and IWC–Z–temperature T relationships for accurate retrievals of IWC from radar in space or at ground-based sites, in the framework of the forthcoming CloudSat spaceborne radar, and of the European CloudNET and U.S. Atmospheric Radiation Measurement Program projects. For this purpose, a large airborne in situ microphysical database is used to perform a detailed error analysis of the IWC–Z and IWC–Z–T methods. This error analysis does not include the error resulting from the mass–dimension relationship assumed in these methods, although the expected magnitude of this error is bounded in the paper. First, this study reveals that the use of a single IWC–Z relationship to estimate IWC at global scale would be feasible up to −15 dBZ, but for larger reflectivities (and therefore larger IWCs) different sets of relationships would have to be used for midlatitude and tropical ice clouds. New IWC–Z and IWC–Z–T relationships are then developed from the large aircraft database and by splitting this database into midlatitude and tropical subsets, and an error analysis is performed. For the IWC–Z relationships, errors decrease roughly linearly from +210%/−70% for IWC = 10−4 g m−3 to +75%/−45% for IWC = 10−2 g m−3, are nearly constant (+50%/−33%) for the intermediate IWCs (0.03–1 g m−3), and then linearly increase up to +210%/−70% for the largest IWCs. The error curves have the same shape for the IWC–Z–T relationships, with a general reduction of errors with respect to the IWC–Z relationships. Comparisons with radar–lidar retrievals confirm these findings. The main improvement brought by the use of temperature as an additional constraint to the IWC retrieval is to reduce both the systematic overestimation and rms differences of the small IWCs (IWC < 0.01 g m−3). For the large IWCs, the use of temperature also results in a slight reduction of the rms differences but in a substantial reduction (by a factor of 2) of the systematic underestimation of the large IWCs, probably owing to a better account of the Mie effect when IWC–Z relationships are stratified by temperature.
Abstract
The objective of this paper is to assess the performances of the proposed ice water content (IWC)–radar reflectivity Z and IWC–Z–temperature T relationships for accurate retrievals of IWC from radar in space or at ground-based sites, in the framework of the forthcoming CloudSat spaceborne radar, and of the European CloudNET and U.S. Atmospheric Radiation Measurement Program projects. For this purpose, a large airborne in situ microphysical database is used to perform a detailed error analysis of the IWC–Z and IWC–Z–T methods. This error analysis does not include the error resulting from the mass–dimension relationship assumed in these methods, although the expected magnitude of this error is bounded in the paper. First, this study reveals that the use of a single IWC–Z relationship to estimate IWC at global scale would be feasible up to −15 dBZ, but for larger reflectivities (and therefore larger IWCs) different sets of relationships would have to be used for midlatitude and tropical ice clouds. New IWC–Z and IWC–Z–T relationships are then developed from the large aircraft database and by splitting this database into midlatitude and tropical subsets, and an error analysis is performed. For the IWC–Z relationships, errors decrease roughly linearly from +210%/−70% for IWC = 10−4 g m−3 to +75%/−45% for IWC = 10−2 g m−3, are nearly constant (+50%/−33%) for the intermediate IWCs (0.03–1 g m−3), and then linearly increase up to +210%/−70% for the largest IWCs. The error curves have the same shape for the IWC–Z–T relationships, with a general reduction of errors with respect to the IWC–Z relationships. Comparisons with radar–lidar retrievals confirm these findings. The main improvement brought by the use of temperature as an additional constraint to the IWC retrieval is to reduce both the systematic overestimation and rms differences of the small IWCs (IWC < 0.01 g m−3). For the large IWCs, the use of temperature also results in a slight reduction of the rms differences but in a substantial reduction (by a factor of 2) of the systematic underestimation of the large IWCs, probably owing to a better account of the Mie effect when IWC–Z relationships are stratified by temperature.
Abstract
In this paper, statistical properties of rainfall are derived from 14 years of Tropical Rainfall Measuring Mission data to optimize the use of flight hours for the upcoming High Altitude Ice Crystals (HAIC)/High Ice Water Content (HIWC) program. This program aims to investigate the convective processes responsible for the generation of the high ice water content that has been recognized as a threat to civil aviation. The probability that convective cells are conducive to HIWC is also further investigated using three years of C-band polarimetric radar data. Further insights into the variability of convective rainfall and favorable conditions for HIWC are also gained using two different methods to characterize the large-scale atmospheric conditions around Darwin, Australia (the Madden–Julian oscillation and the Darwin atmospheric regimes), and the underlying surface type (oceanic vs continental). The main results from the climatology relevant to flight-plan decision making are (i) convective cells conducive to HIWC should be found close to Darwin, (ii) at least 90% of convective cells are conducive to HIWC at 10- and 12-km flight levels, (iii) multiple flights per day in favorable large-scale conditions will be needed so as to utilize the 150 project flight hours, (iv) the largest numbers of HIWC radar pixels are found around 0300 and 1500 local time, and (v) to fulfill the requirement to fly 90 h in oceanic convection and 60 h in or around continental convection, a minimum “acceptable” size of the convective area has been derived and should serve as a guideline for flight-decision purposes.
Abstract
In this paper, statistical properties of rainfall are derived from 14 years of Tropical Rainfall Measuring Mission data to optimize the use of flight hours for the upcoming High Altitude Ice Crystals (HAIC)/High Ice Water Content (HIWC) program. This program aims to investigate the convective processes responsible for the generation of the high ice water content that has been recognized as a threat to civil aviation. The probability that convective cells are conducive to HIWC is also further investigated using three years of C-band polarimetric radar data. Further insights into the variability of convective rainfall and favorable conditions for HIWC are also gained using two different methods to characterize the large-scale atmospheric conditions around Darwin, Australia (the Madden–Julian oscillation and the Darwin atmospheric regimes), and the underlying surface type (oceanic vs continental). The main results from the climatology relevant to flight-plan decision making are (i) convective cells conducive to HIWC should be found close to Darwin, (ii) at least 90% of convective cells are conducive to HIWC at 10- and 12-km flight levels, (iii) multiple flights per day in favorable large-scale conditions will be needed so as to utilize the 150 project flight hours, (iv) the largest numbers of HIWC radar pixels are found around 0300 and 1500 local time, and (v) to fulfill the requirement to fly 90 h in oceanic convection and 60 h in or around continental convection, a minimum “acceptable” size of the convective area has been derived and should serve as a guideline for flight-decision purposes.
Abstract
Best estimates of the bulk microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration) are derived for three case studies of tropical ice clouds sampled during the Tropical Warm Pool International Cloud Experiment (TWP-ICE). Two case studies are aged cirrus clouds produced by deep convection (the so-called 27/01 and 29/01 cases), and the third (“02/02”) is a fresh anvil produced by deep convective activity over the Tiwi Islands. Using crystal images obtained by a Cloud Particle Imager (CPI), it is observed that small ice particles (with maximum dimension D < 50–100 μm) were predominantly quasi spherical, with the degree of nonsphericity increasing rapidly in the 50 < D < 100-μm range. For D > 100 μm, the aged cirrus clouds were predominantly characterized by bullet rosettes and aggregates of bullet rosettes, plates, and columns. In contrast, the fresh anvil had more frequent occurrences of plates, columns, aggregates of plates, and occasionally capped columns. The impact of shattering of large ice crystals on probe tips and the overall quality of the TWP-ICE in situ microphysical measurements are assessed. It is suggested that shattering has a relatively small impact on the CPI and cloud droplet probe (CDP) TWP-ICE data and a large impact on the Cloud Aerosol Spectrometer data, as already documented by others. It is also shown that the CPI size distributions must be multiplied by a factor of 4 to match those of the cloud imaging probe (CIP) for maximum dimension larger than 100 μm (taken as a reference). A technique [named Best Estimate of Area and Density (BEAD)] to minimize errors associated with the density (ρ)–D and projected area (A)–D assumptions in bulk microphysics calculation is introduced and applied to the TWP-ICE data. The method makes direct use of the frequency of occurrence of each particle habit as classified from the CPI data and prescribed ρ–D and A–D relationships from the literature. This approach produces ice water content (IWC) estimates that are virtually unbiased relative to bulk measures obtained from a counterflow spectrometer and impactor (CSI) probe. In contrast, the use of ρ–D and A–D relationships for single habits does produce large biases relative to the CSI observations: from −50% for bullet rosettes to +70%–80% for aggregates. The so-called width, length, area, and perimeter (WLAP) technique, which also makes use of individual CPI images, is found to produce positively biased IWCs (by 40% or so), and has a standard deviation of the errors similar to the BEAD technique. The impact of the large variability of the size distributions measured by different probe combinations on the bulk microphysical properties is characterized. The mean fractional differences with respect to the CSI measurements are small for the CPI + CIP, CPI, and CDP + CIP combinations (2.2%, −0.8%, and −1.1%, respectively), with standard deviations of the fractional differences ranging from 7% to 9%. This result provides an independent validation of the CPI scaling factor. The fractional differences produced between the CPI + CIP, CPI, and CDP + CIP combinations for extinction, effective radius, and total concentration are 33%, 10%–20%, and 90%, respectively, with relatively small standard deviations of 5%–8%. The fractional difference on total concentration varies greatly over the concentration range though, with values being larger than a factor of 2 for total concentrations smaller than 40 L−1, but reducing to 10%–20% for concentrations larger than 100 L−1. Therefore, caution should be exercised when using total concentrations smaller than 60–80 L−1 as references for radar–lidar retrieval evaluation.
Abstract
Best estimates of the bulk microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration) are derived for three case studies of tropical ice clouds sampled during the Tropical Warm Pool International Cloud Experiment (TWP-ICE). Two case studies are aged cirrus clouds produced by deep convection (the so-called 27/01 and 29/01 cases), and the third (“02/02”) is a fresh anvil produced by deep convective activity over the Tiwi Islands. Using crystal images obtained by a Cloud Particle Imager (CPI), it is observed that small ice particles (with maximum dimension D < 50–100 μm) were predominantly quasi spherical, with the degree of nonsphericity increasing rapidly in the 50 < D < 100-μm range. For D > 100 μm, the aged cirrus clouds were predominantly characterized by bullet rosettes and aggregates of bullet rosettes, plates, and columns. In contrast, the fresh anvil had more frequent occurrences of plates, columns, aggregates of plates, and occasionally capped columns. The impact of shattering of large ice crystals on probe tips and the overall quality of the TWP-ICE in situ microphysical measurements are assessed. It is suggested that shattering has a relatively small impact on the CPI and cloud droplet probe (CDP) TWP-ICE data and a large impact on the Cloud Aerosol Spectrometer data, as already documented by others. It is also shown that the CPI size distributions must be multiplied by a factor of 4 to match those of the cloud imaging probe (CIP) for maximum dimension larger than 100 μm (taken as a reference). A technique [named Best Estimate of Area and Density (BEAD)] to minimize errors associated with the density (ρ)–D and projected area (A)–D assumptions in bulk microphysics calculation is introduced and applied to the TWP-ICE data. The method makes direct use of the frequency of occurrence of each particle habit as classified from the CPI data and prescribed ρ–D and A–D relationships from the literature. This approach produces ice water content (IWC) estimates that are virtually unbiased relative to bulk measures obtained from a counterflow spectrometer and impactor (CSI) probe. In contrast, the use of ρ–D and A–D relationships for single habits does produce large biases relative to the CSI observations: from −50% for bullet rosettes to +70%–80% for aggregates. The so-called width, length, area, and perimeter (WLAP) technique, which also makes use of individual CPI images, is found to produce positively biased IWCs (by 40% or so), and has a standard deviation of the errors similar to the BEAD technique. The impact of the large variability of the size distributions measured by different probe combinations on the bulk microphysical properties is characterized. The mean fractional differences with respect to the CSI measurements are small for the CPI + CIP, CPI, and CDP + CIP combinations (2.2%, −0.8%, and −1.1%, respectively), with standard deviations of the fractional differences ranging from 7% to 9%. This result provides an independent validation of the CPI scaling factor. The fractional differences produced between the CPI + CIP, CPI, and CDP + CIP combinations for extinction, effective radius, and total concentration are 33%, 10%–20%, and 90%, respectively, with relatively small standard deviations of 5%–8%. The fractional difference on total concentration varies greatly over the concentration range though, with values being larger than a factor of 2 for total concentrations smaller than 40 L−1, but reducing to 10%–20% for concentrations larger than 100 L−1. Therefore, caution should be exercised when using total concentrations smaller than 60–80 L−1 as references for radar–lidar retrieval evaluation.
Abstract
The paper describes an original method that is complementary to the radar–lidar algorithm method to characterize ice cloud properties. The method makes use of two measurements from a Doppler cloud radar (35 or 95 GHz), namely, the radar reflectivity and the Doppler velocity, to recover the effective radius of crystals, the terminal fall velocity of hydrometeors, the ice water content, and the visible extinction from which the optical depth can be estimated. This radar method relies on the concept of scaling the ice particle size distribution. An error analysis using an extensive in situ airborne microphysical database shows that the expected errors on ice water content and extinction are around 30%–40% and 60%, respectively, including both a calibration error and a bias on the terminal fall velocity of the particles, which all translate into errors in the retrieval of the density–diameter and area–diameter relationships. Comparisons with the radar–lidar method in areas sampled by the two instruments also demonstrate the accuracy of this new method for retrieval of the cloud properties, with a roughly unbiased estimate of all cloud properties with respect to the radar–lidar method. This method is being systematically applied to the cloud radar measurements collected over the three-instrumented sites of the European Cloudnet project to validate the representation of ice clouds in numerical weather prediction models and to build a cloud climatology.
Abstract
The paper describes an original method that is complementary to the radar–lidar algorithm method to characterize ice cloud properties. The method makes use of two measurements from a Doppler cloud radar (35 or 95 GHz), namely, the radar reflectivity and the Doppler velocity, to recover the effective radius of crystals, the terminal fall velocity of hydrometeors, the ice water content, and the visible extinction from which the optical depth can be estimated. This radar method relies on the concept of scaling the ice particle size distribution. An error analysis using an extensive in situ airborne microphysical database shows that the expected errors on ice water content and extinction are around 30%–40% and 60%, respectively, including both a calibration error and a bias on the terminal fall velocity of the particles, which all translate into errors in the retrieval of the density–diameter and area–diameter relationships. Comparisons with the radar–lidar method in areas sampled by the two instruments also demonstrate the accuracy of this new method for retrieval of the cloud properties, with a roughly unbiased estimate of all cloud properties with respect to the radar–lidar method. This method is being systematically applied to the cloud radar measurements collected over the three-instrumented sites of the European Cloudnet project to validate the representation of ice clouds in numerical weather prediction models and to build a cloud climatology.
Abstract
A spatial mismatch between radar-based hail swaths and surface hail reports is commonly noted in meteorological literature. The discrepancy is partly due to hailstone advection and melting between detection aloft and observation at the ground. This study aims to mitigate this problem by introducing a model named HailTrack, which estimates hailfall at the surface using radar observations. The model operates by detecting, tracking, and collating hailstone trajectories using dual-polarized, dual-Doppler radar retrievals. Notable improvements in hailfall forecasts were observed through the use of HailTrack, and initializing the model with radar retrievals of hail differential reflectivity H DR was found to produce the most accurate hailfall estimates. The analysis of a case study in Brisbane, Australia, demonstrated that trajectory modeling significantly improved the correlation between hail swaths and hail-related insurance losses, increasing Heidke skill scores from 0.48 to 0.58. The accumulated kinetic energy of hailstone impacts also showed some skill in identifying areas that were exposed to particularly severe hailfall. Other unique impact estimates are presented, such as hailstone advection information and hailstone impact angle statistics. The potential to run the model in real time and produce short-term (10–15 min) nowcasts is also introduced. Model applications include improving radar-based hail climatologies, validating hail detection techniques and insurance claims data, and providing real-time hail impact maps to improve public awareness of hail risk.
Abstract
A spatial mismatch between radar-based hail swaths and surface hail reports is commonly noted in meteorological literature. The discrepancy is partly due to hailstone advection and melting between detection aloft and observation at the ground. This study aims to mitigate this problem by introducing a model named HailTrack, which estimates hailfall at the surface using radar observations. The model operates by detecting, tracking, and collating hailstone trajectories using dual-polarized, dual-Doppler radar retrievals. Notable improvements in hailfall forecasts were observed through the use of HailTrack, and initializing the model with radar retrievals of hail differential reflectivity H DR was found to produce the most accurate hailfall estimates. The analysis of a case study in Brisbane, Australia, demonstrated that trajectory modeling significantly improved the correlation between hail swaths and hail-related insurance losses, increasing Heidke skill scores from 0.48 to 0.58. The accumulated kinetic energy of hailstone impacts also showed some skill in identifying areas that were exposed to particularly severe hailfall. Other unique impact estimates are presented, such as hailstone advection information and hailstone impact angle statistics. The potential to run the model in real time and produce short-term (10–15 min) nowcasts is also introduced. Model applications include improving radar-based hail climatologies, validating hail detection techniques and insurance claims data, and providing real-time hail impact maps to improve public awareness of hail risk.
Abstract
The objective of this paper is to investigate whether estimates of the cloud frequency of occurrence and associated cloud radiative forcing as derived from ground-based and satellite active remote sensing and radiative transfer calculations can be reconciled over a well-instrumented active remote sensing site located in Darwin, Australia, despite the very different viewing geometry and instrument characteristics. It is found that the ground-based radar–lidar combination at Darwin does not detect most of the cirrus clouds above 10 km (because of limited lidar detection capability and signal obscuration by low-level clouds) and that the CloudSat radar–Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) combination underreports the hydrometeor frequency of occurrence below 2-km height because of instrument limitations at these heights. The radiative impact associated with these differences in cloud frequency of occurrence is large on the surface downwelling shortwave fluxes (ground and satellite) and the top-of-atmosphere upwelling shortwave and longwave fluxes (ground). Good agreement is found for other radiative fluxes. Large differences in radiative heating rate as derived from ground and satellite radar–lidar instruments and radiative transfer calculations are also found above 10 km (up to 0.35 K day−1 for the shortwave and 0.8 K day−1 for the longwave). Given that the ground-based and satellite estimates of cloud frequency of occurrence and radiative impact cannot be fully reconciled over Darwin, caution should be exercised when evaluating the representation of clouds and cloud–radiation interactions in large-scale models, and limitations of each set of instrumentation should be considered when interpreting model–observation differences.
Abstract
The objective of this paper is to investigate whether estimates of the cloud frequency of occurrence and associated cloud radiative forcing as derived from ground-based and satellite active remote sensing and radiative transfer calculations can be reconciled over a well-instrumented active remote sensing site located in Darwin, Australia, despite the very different viewing geometry and instrument characteristics. It is found that the ground-based radar–lidar combination at Darwin does not detect most of the cirrus clouds above 10 km (because of limited lidar detection capability and signal obscuration by low-level clouds) and that the CloudSat radar–Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) combination underreports the hydrometeor frequency of occurrence below 2-km height because of instrument limitations at these heights. The radiative impact associated with these differences in cloud frequency of occurrence is large on the surface downwelling shortwave fluxes (ground and satellite) and the top-of-atmosphere upwelling shortwave and longwave fluxes (ground). Good agreement is found for other radiative fluxes. Large differences in radiative heating rate as derived from ground and satellite radar–lidar instruments and radiative transfer calculations are also found above 10 km (up to 0.35 K day−1 for the shortwave and 0.8 K day−1 for the longwave). Given that the ground-based and satellite estimates of cloud frequency of occurrence and radiative impact cannot be fully reconciled over Darwin, caution should be exercised when evaluating the representation of clouds and cloud–radiation interactions in large-scale models, and limitations of each set of instrumentation should be considered when interpreting model–observation differences.
Abstract
In this paper, unprecedented bulk measurements of ice water content (IWC) up to approximately 5 g m−3 and 95-GHz radar reflectivities Z 95 are used to analyze the statistical relationship between these two quantities and its variability. The unique aspect of this study is that these IWC–Z 95 relationships do not use assumptions on cloud microphysics or backscattering calculations. IWCs greater than 2 g m−3 are also included for the first time in such an analysis, owing to improved bulk IWC probe technology and a flight program targeting high ice water content. Using a single IW–Z 95 relationship allows for the retrieval of IWC from radar reflectivities with less than 30% bias and 40%–70% rms difference. These errors can be reduced further, down to 10%–20% bias over the whole IWC range, using the temperature variability of this relationship. IWC errors largely increase for Z 95 > 16 dBZ, as a result of the distortion of the IWC–Z 95 relationship by non-Rayleigh scattering effects. A nonlinear relationship is proposed to reduce these errors down to 20% bias and 20%–35% rms differences. This nonlinear relationship also outperforms the temperature-dependent IWC–Z 95 relationship for convective profiles. The joint frequency distribution of IWC and temperature within and around deep tropical convective cores shows that at the −50° ± 5°C level, the cruise altitude of many commercial jet aircraft, IWCs greater than 1.5 g m−3 were found exclusively in convective profiles.
Abstract
In this paper, unprecedented bulk measurements of ice water content (IWC) up to approximately 5 g m−3 and 95-GHz radar reflectivities Z 95 are used to analyze the statistical relationship between these two quantities and its variability. The unique aspect of this study is that these IWC–Z 95 relationships do not use assumptions on cloud microphysics or backscattering calculations. IWCs greater than 2 g m−3 are also included for the first time in such an analysis, owing to improved bulk IWC probe technology and a flight program targeting high ice water content. Using a single IW–Z 95 relationship allows for the retrieval of IWC from radar reflectivities with less than 30% bias and 40%–70% rms difference. These errors can be reduced further, down to 10%–20% bias over the whole IWC range, using the temperature variability of this relationship. IWC errors largely increase for Z 95 > 16 dBZ, as a result of the distortion of the IWC–Z 95 relationship by non-Rayleigh scattering effects. A nonlinear relationship is proposed to reduce these errors down to 20% bias and 20%–35% rms differences. This nonlinear relationship also outperforms the temperature-dependent IWC–Z 95 relationship for convective profiles. The joint frequency distribution of IWC and temperature within and around deep tropical convective cores shows that at the −50° ± 5°C level, the cruise altitude of many commercial jet aircraft, IWCs greater than 1.5 g m−3 were found exclusively in convective profiles.
Abstract
This study addresses clouds with significant ice water content (IWC) in the stratiform regions downwind of the convective cores of African squall lines in the framework of the French–Indian satellite Megha-Tropiques project, observed in August 2010 next to Niamey (13.5°N, 2°E) in the southwestern part of Niger. The objectives included comparing the IWC–Z reflectivity relationship for precipitation radars in deep stratiform anvils, collocating reflectivity observed from ground radar with the calculated reflectivity from in situ microphysics for all aircraft locations inside the radar range, and interpreting the role of large ice crystals in the reflectivity of centimeter radars through analysis of their microphysical characteristics as ice crystals larger than 5 mm frequently occurred. It was found that, in the range of 20–30 dBZ, IWC and C-band reflectivity are not really correlated. Cloud regions with high IWC caused by important crystal number concentrations can lead to the same reflectivity factor as cloud regions with low IWC formed by a few millimeter-sized ice crystals.
Abstract
This study addresses clouds with significant ice water content (IWC) in the stratiform regions downwind of the convective cores of African squall lines in the framework of the French–Indian satellite Megha-Tropiques project, observed in August 2010 next to Niamey (13.5°N, 2°E) in the southwestern part of Niger. The objectives included comparing the IWC–Z reflectivity relationship for precipitation radars in deep stratiform anvils, collocating reflectivity observed from ground radar with the calculated reflectivity from in situ microphysics for all aircraft locations inside the radar range, and interpreting the role of large ice crystals in the reflectivity of centimeter radars through analysis of their microphysical characteristics as ice crystals larger than 5 mm frequently occurred. It was found that, in the range of 20–30 dBZ, IWC and C-band reflectivity are not really correlated. Cloud regions with high IWC caused by important crystal number concentrations can lead to the same reflectivity factor as cloud regions with low IWC formed by a few millimeter-sized ice crystals.